• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.269-279
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• 2024

The study explores the evolving landscape of overseas expansion strategies by Korean corporations, focusing on recent geopolitical tensions, the COVID-19 pandemic, and disruptions in global supply chains. It emphasizes the challenges faced by industries producing high-value products and delves into the concept of "Friend-Shoring" policies in the United States, leading major Korean companies to invest in local semiconductor, battery, and automotive factories. Recognizing the potential fragmentation of Korea's manufacturing sector, the paper introduces the "Mother Factory" strategy as a policy initiative, inspired by Japan's model, to establish core production facilities domestically. The discussion unfolds by examining the cases of major companies in Japan and the United States, highlighting the need for Korea to adopt a mother factory strategy to mitigate risks associated with friend-shoring policies. Inspired by Intel's "Copy Exactly" approach, the paper proposes a Korean mother factory model integrating smart factory technology and digital twin systems. This strategic shift aims to enhance responsiveness to geopolitical challenges and fortify the competitiveness of Korean high-tech industries. Finally, the paper proposes a Korean Mother Factory based on smart factory concepts. The suggested model integrates smart factory technology and digital twin frameworks to enhance responsiveness and fortify competitiveness. In conclusion, the paper advocates for the adoption of a comprehensive Korean Mother Factory model to address contemporary challenges, foster advanced manufacturing, and ensure the sustainability and competitiveness of Korean high-tech industries in the global landscape. The proposed strategy aligns with the evolving dynamics of the manufacturing sector and emphasizes technological advancements, collaboration, and strategic realignment.

• The Journal of Economics, Marketing and Management
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• v.11 no.6
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• pp.43-55
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• 2023

Purpose: The purpose of this study was to identify the relationship between smart factory utilization and continued use intention between UTAUT, dynamic capabilities of smart factory construction companies and present the company's strategic direction. Research design, data, and methodology: In this study, a structured research model was derived to confirm the relationship between UTAUT, dynamic capabilities, smart factory utilization and continued use intention and the difference according to Technology perception. For analysis a total of 223 valid questionnaires from e-commerce users were used. Confirmatory factor analysis, correlation analysis, and structural equations were conducted to verify. Results: Both UTAUT, dynamic capabilities had a significant effect on smart factory utilization as well as continued use intention. It was found that the relationship between UTAUT, dynamic capabilities, smart factory utilization, and continued use intention. differed depending on the technology perception. Conclusions: Organizational members utilize the smart factory in anticipation of effects such as work performance and various improvements. Smart factory data will be used continuously when it is useful for business processes and operations. It is necessary to establish strategies and provide training to improve the technical level and capabilities of organizational members. Through this, a strategy is needed that can be continuously used by utilizing the information obtained through smart factory to improve work efficiency, productivity and efficiency increase is needed

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.351-356
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• 2007

Factory location selection is very important to the success of operation of the whole supply chain, but few effective solutions exist to deliver a good result, motivated by this, this paper tries to introduce a new factory location selection methodology by employing the artificial neural networks technology. First, we reviewed previous research related to factory location selection problems, and then developed a (neural network-based factory selection model) NNFSM which adopted back-propagation neural network theory, next, we developed computer program using C++ to demonstrate our proposed model. then we did case study by choosing a Korean steelmaking company P to show how our proposed model works,. Finnaly, we concluded by highlighting the key contributions of this paper and pointing out the limitations and future research directions of this paper. Compared to other traditional factory location selection methods, our proposed model is time-saving; more efficient.and can produce a much better result.

• Journal of Industrial Technology
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• v.22 no.B
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• pp.79-88
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• 2002

This paper deals with a case study on the process improvement and the layout design of a boiler factory with FactoryCAD. Firstly, two alternatives of job reallocation are suggested with the understanding of problems in current process. The layout planning for these new alternatives is carried out by simple procedure and the detailed analyses are performed by the aid of FactoryCAD program. The result shows that the new layout plan brings on about 10% reduction of travel distance. The utilization of FactoryCAD program can simplify the process of layout design.

• International Journal of CAD/CAM
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• v.2 no.1
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• pp.39-44
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• 2002

This paper presents a structure and architecture of an integrated simulation method (ISM) to meet the requirements of virtual factory engineering (VFE). Combining CAD, VR and discrete event simulation techniques, the ISM provides static and dynamic simulation functions for implementation of VFE throughout the lifecycle. The static simulation can be used to evaluate the factory layout. The dynamic simulation enables us to evaluate ergonomics of factory, process performance of production system, feasibility of production plan and operation of factory, and to train operators safely, which cover the whole VFE lifecycle. The principles of the key techniques of VFE, including virtual factory data management system (VFDMS), static and dynamic simulation, are also discussed. To demonstrate and validate the ISM, a case study has been carried out in an assembly factory.

• IE interfaces
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• v.16 no.1
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• pp.63-69
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• 2003

Virtual Manufacturing is a technology facilitating effective development and agile production of products via computer models representing physical and logical schema and the behavior of the real manufacturing systems including manufacturing resources, environments and products. For the successful application of this technology, a virtual factory as a well-designed and integrated environment is essential. To construct a virtual factory in effective and concurrent manners, a supporting information infrastructure for managing diverse models of virtual factory is very important. In this paper, we constructed the web-based information management system for many engineering activities related with a virtual factory. Using this system, users can handle all information and diverse digital files including attributes, parameters, 3-D CAD files, simulation models, and etc. of a cell, line and whole factory. We expect that this information management system for a virtual factory helps us achieve great time savings and advances in accuracy for construction and maintenance activities of virtual factories.

• Korean Architects
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• no.7 s.459
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• pp.48-53
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• 2007

Amisak is a rechargeable tool company and is aiming to be a leading company in Korea by 2010. Ochang factory will be a base for this aim. Client's bad experience in construction of their first Suwon factory and my regretable memory of 1996 design & construction of BTC factory in Whasung lead us to desire for an outstandingly good factory. Total floor area is about 5,000 square. meter (1,500 py) and it has been designed with 3 different facilities, Factory (steel structure, 2 levels), Office (RC structure, 3 levels), and Welfare (RC structure, 3 levels including basement). Factory area is expected to expand its facility at the rear end within 3 to 5 years. Aimsak Ochang factory is expected to be completed in December 2007.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.42-48
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• 2022

Currently, the world is facing severe inflation due to Corona and the war in Ukraine, and it is causing a lot of difficulties for us. Companies are facing a lot of restrictions on their economic activities compared to the past due to supply chain problems and foreign exchange rates. In this situation, many countries have been implementing various smart factory promotion projects to secure competitiveness through productivity improvement in the manufacturing industry. In this study, the contents of smart factory promotion in major countries were reviewed, and problems raised about the implementation of smart factory in Korea, which are being implemented based on this, were described. It is most reasonable to judge the success of a smart factory by the achievement of the performance indicators presented at the time of the project. Therefore, based on the performance index of the business, which is a key factor in determining the success or failure of a smart factory, we investigated whether the company's smart factory promotion can be carried out successfully through examples

• International journal of advanced smart convergence
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• v.11 no.1
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• pp.42-47
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• 2022

As smart factory is the factory which produces the products according to the customer's diverse demand and the changing conditions in it, it can be characterized by flexible production, dynamic reconstruction, and optimized production environment. To implement these characteristics, many kind of configuration elements in the smart factory should be connected to and communicated with each other. So the network is responsible for playing this role in the smart factory. As SDN (Software Defined Network) is the technology that can dynamically cope with the explosive increasing data amount and the hourly changing network condition, it is one of network technologies that can be applied to the smart factory. In this paper, we address SDN function and operation, SDN model suitable for the smart factory, and then performs the simulation for measuring this model.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.107-115
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• 2017

Recently, much attention in building smart factory have been dramatically increased. Despite the growing interest in smart factory, few guidelines exist how to successfully build smart factory. The purpose of this study is to investigate successful cases in building smart factory in Korea. Drawing on the analysis of successful cases, we suggest the valuable guidelines and directions toward success of smart factory. As a result, in the case of large-size firms, it is an effective strategy that expanding from a model factory to whole factory for successful smart factory building. In addition, in the case of medium and small-size firms, it is an effective strategy that upgrading from low-level step to high-level step for successful smart factory building. Therefore, this study provides companies and government with specific and practical success strategies as well as industrial policy improvements.